Analysis of the mean squared derivative cost function

In this paper, we investigate the mean squared derivative cost functions that arise in various applications such as in motor control, biometrics and optimal transport theory. We provide qualitative properties, explicit analytical formulas and computational algorithms for the cost functions. We also perform numerical simulations to illustrate the analytical results. In addition, as a by-product of our analysis, we obtain an explicit formula for the inverse of a Wronskian matrix that is of independent interest in linear algebra and differential equations theory.Comment: 28 page

The F@ Framework of Designing Awareness Mechanisms in Instant Messaging

This paper presents our research on awareness support in Instant Messaging (IM). The paper starts with a brief overview of empirical study of IM, using an online survey and face-to-face interviews to identify user needs for awareness support. The study identified a need for supporting four aspects of awareness, awareness of multiple concurrent conversations, conversational awareness, presence awareness of a group conversation, and visibility of moment-to-moment listeners and viewers. Based on the empirical study and existing research on awareness, we have developed the F@ (read as fat) framework of awareness. F@ comprises of the abstract level and the concrete level. The former includes an in-depth description of various awareness aspects in IM, whilst the latter utilises temporal logic to formalise fundamental time-related awareness aspects. F@ helps developers gain a better understanding of awareness and thereby design usable mechanisms to support awareness. Applying F@, we have designed several mechanisms to support various aspect of awareness in IM

The effect of phytohormones on the flowering of plants

During the development of angiosperms, one of the most critical stages of plants is the transition from vegetative to reproductive stage, and successfully producing seeds is necessary. Plants have developed a complex signaling pathway to recognize and combine endogenous and environmental signals. Plant growth regulators (PGRs) play a role in regulating flower growth on shoots. Physiological and biochemical processes work together to differentiate and produce flower buds. The impact of PGRs on floral bud differentiation has been the subject of several publications in recent years. In addition, the dynamic variations in gibberellin (GA), auxin, and cytokinin levels in buds and the hormonal-related signatures in gene regulatory networks indicate a crucial function for these hormones during floral bud development in plants. Especially the flowering hormone GA has a key role in regulating the activities related to flowering genes as well as controlling the activity of the DELLA protein. Abscisic acid (ABA) and ethylene (ET) have an inhibitory role in flowering but in some cases stimulate flowering depending on environmental conditions. This study aims to understand the regulation of phytohormones on flowering of plants and its effects on plant development during the flowering stage

Ion Irradiation-induced nano-crystallization metallic glasses (amorphous metal)

This project idea is proposed in order to develop the understanding of the mechanisms responsible for Nano-crystal phase formation when metallic glasses (amorphous) is exposed under the high energy ion irradiation and is quantified the resulting effects on the material behavior. The objectives of this project are to: (1) quantify the response of metallic glasses to ion irradiation, specifically, damage cascade formation and subsequent structural evolutions along ion tracks, (2) identify the mechanisms responsible for ion irradiation-induced Nano-crystallization, specifically, the paths of crystal nucleation and growth, and effects of energy deposition rate and subsequent energy dissipation rate on crystal formation, (3) quantify the resulting crystal phases, densities and distribution under different ion irradiation conditions and identify the governing factors to reach controllable crystal formation, and (4) measure the hardness elastic modulus and ductility of the metallic glasses containing Nano-crystals created by ion irradiation, and quantify shear band interactions with crystal of different sizes, shapes and matrix distribution. It is expected that this study will contribute to new fundamental understanding of mechanisms responsible for the creation of Nano-crystals in metallic glasses by ion irradiation, and the role of the altered structure in the modification of the materials mechanical response. It will impact fundamental understanding in several materials science subfields. In the field of ion-solid interactions, phase transitions from amorphous to crystalline in metallic materials are poorly understood. This study will contribute to a more complete understanding of the structural evolution occurring over different time scales involving damage cascade creation, thermal spike formation, and structural relaxation. The roles of excess free volume and thermal energy deposition on the mechanisms responsible for Nano-crystal phase formation will be identified. In the field of Nano-mechanical behavior of materials, this study will identify the roles of Nano-crystals on the mechanical response of metallic glasses. It will further contribute to our understanding of shear band nucleation and propagation, and deflection and attenuation by Nano-crystals of different mechanical strengths and interaction cross sections

A Back Propagation Neural Network Model with the Synthetic Minority Over-Sampling Technique for Construction Company Bankruptcy Prediction

Improving model accuracy is one of the most frequently addressed issues in bankruptcy prediction. Several previous studies employed artificial neural networks (ANNs) to improve the accuracy at which construction company bankruptcy can be predicted. However, most of these studies use the sample-matching technique and all of the available company quarters or company years in the dataset, resulting in sample selection biases and between-class imbalances. This study integrates a back propagation neural network (BPNN) with the synthetic minority over-sampling technique (SMOTE) and the use of all of the available company-year samples during the sample period to improve the accuracy at which bankruptcy in construction companies can be predicted. In addition to eliminating sample selection biases during the sample matching and between-class imbalance, these methods also achieve the high accuracy rates. Furthermore, the approach used in this study shows optimal over-sampling times, neurons of the hidden layer, and learning rate, all of which are major parameters in the BPNN and SMOTE-BPNN models. The traditional BPNN model is provided as a benchmark for evaluating the predictive abilities of the SMOTE-BPNN model. The empirical results of this paper show that the SMOTE-BPNN model outperforms the traditional BPNN

On the distribution of the number of internal equilibria in random evolutionary games

In this paper, we study the distribution of the number of internal equilibria of a multi-player two-strategy random evolutionary game. Using techniques from the random polynomial theory, we obtain a closed formula for the probability that the game has a certain number of internal equilibria. In addition, by employing Descartes' rule of signs and combinatorial methods, we provide useful estimates for this probability. Finally, we also compare our analytical results with those obtained from samplings.Comment: 31 pages, comments are welcome. arXiv admin note: substantial text overlap with arXiv:1708.0167

Exotic States Emerged By Spin-Orbit Coupling, Lattice Modulation and Magnetic Field in Lieb Nano-ribbons

The Lieb nano-ribons with the spin-orbit coupling, the lattice modulation and the magnetic field are exactly studied. They are constructed from the Lieb lattice with two open boundaries in a direction. The interplay between the spin-orbit coupling, the lattice modulation and the magnetic field emerges various exotic ground states. With certain conditions of the spin-orbit coupling, the lattice modulation, the magnetic field and filling the ground state becomes half metallic or half topological. In the half metallic ground state, one spin component is metallic, while the other spin component is insulating. In the half topological ground state, one spin component is topological, while the other spin component is topological trivial. The model exhibits very rich phase diagram

Determinants Influencing Liquidity of Listed Steel Firms in Vietnam

This study is conducted to investigate the impact levels of determinants influencing liquidity of listed steel firms on Vietnam Stock Exchange. Data were collected from audited financial statements of 25 listed food processing firms from 2014 to 2017. This research employs the least squares method (OLS) and tests to determine the influence of factors on the liquidity of listed sample firms. The results indicate that return on assets (ROA), operating period (AGE) and asset structure (AS) have positive impacts on the liquidity. In contrast, the firm size and debt ratio has the opposite effects. Based on the findings, a number of recommendations are proposed to increase the liquidity ratio of listed firms in the future. Keywords: Liquidity, steel firms, determinants, Vietnam Stock Exchange DOI: 10.7176/EJBM/11-7-10 Publication date:March 31st 201